{"id":3101,"date":"2023-07-19T05:18:21","date_gmt":"2023-07-19T05:18:21","guid":{"rendered":"https:\/\/statorials.org\/tr\/r-vektordeki-degerlere-gore-veri-cercevesindeki-satirlari-secin\/"},"modified":"2023-07-19T05:18:21","modified_gmt":"2023-07-19T05:18:21","slug":"r-vektordeki-degerlere-gore-veri-cercevesindeki-satirlari-secin","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/r-vektordeki-degerlere-gore-veri-cercevesindeki-satirlari-secin\/","title":{"rendered":"C: vekt\u00f6r de\u011ferlerine dayal\u0131 olarak veri \u00e7er\u00e7evesindeki sat\u0131rlar nas\u0131l se\u00e7ilir?"},"content":{"rendered":"

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Bir vekt\u00f6r\u00fcn de\u011ferlerine g\u00f6re R’deki bir veri \u00e7er\u00e7evesinden sat\u0131r se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz:<\/span><\/p>\n

Y\u00f6ntem 1: Base R’yi kullan\u0131n<\/strong><\/span><\/p>\n

 new_df <- df[df$column_name %in%<\/span> values_vector, ]\n<\/strong><\/span><\/pre>\n
 Y\u00f6ntem 2: dplyr paketini kullanma<\/strong><\/span><\/p>\n
 library<\/span> (dplyr)\n\nnew_df <- df %>% filter(column_name %in%<\/span> values_vector)\n<\/strong><\/span><\/pre>\n
 A\u015fa\u011f\u0131daki \u00f6rnekler, R’deki a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesiyle her y\u00f6ntemin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir:<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (division=c('West', 'West', 'East', 'East', 'North'),\n                 points=c(120, 100, 104, 98, 105),\n                 assists=c(30, 35, 64, 28, 23))\n\n#view data frame\n<\/span>df\n\n  assists points division\n1 West 120 30\n2 West 100 35\n3 East 104 64\n4 East 98 28\n5 North 105 23\n<\/strong><\/span><\/pre>\n
 \u00d6rnek 1: Vekt\u00f6r de\u011ferlerine g\u00f6re sat\u0131r se\u00e7mek i\u00e7in R Taban\u0131n\u0131 kullan\u0131n<\/span><\/strong><\/h3>\n
 Orijinal veri \u00e7er\u00e7evesinden yaln\u0131zca b\u00f6lme<\/strong> s\u00fctunundaki de\u011ferin “Bat\u0131” veya “Kuzey”e e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabiliriz.<\/span><\/p>\n
 #define values of interest\nmy_values <- c(' West<\/span> ', ' North<\/span> ')\n\n#select rows that contain 'West' or 'North' in division column\n<\/span>new_df <- df[df$division %in% my_values, ]\n\n#view results\n<\/span>new_df\n\n  assists points division\n1 West 120 30\n2 West 100 35\n5 North 105 23\n<\/span><\/span><\/strong><\/span><\/pre>\n
 Yeni veri \u00e7er\u00e7evesi yaln\u0131zca b\u00f6lme<\/strong> s\u00fctunundaki de\u011feri “Bat\u0131” veya “Kuzey”e e\u015fit olan sat\u0131rlar\u0131 i\u00e7erir.<\/span><\/p>\n
 \u00d6rnek 2: Vekt\u00f6r de\u011ferlerine g\u00f6re sat\u0131rlar\u0131 se\u00e7mek i\u00e7in dplyr’\u0131 kullan\u0131n<\/span><\/strong><\/h3>\n
 Ayr\u0131ca, yaln\u0131zca orijinal veri \u00e7er\u00e7evesindeki b\u00f6lme<\/strong> s\u00fctunundaki de\u011ferin “Bat\u0131” veya “Kuzey”e e\u015fit oldu\u011fu sat\u0131rlar\u0131 se\u00e7mek i\u00e7in R’deki dplyr<\/a> paketindeki filter()<\/strong> i\u015flevini kullanabiliriz.<\/span><\/p>\n
 library<\/span> (dplyr)<\/span>\n\n#define values of interest\nmy_values <- c(' West<\/span> ', ' North<\/span> ')\n\n#select rows that contain 'West' or 'North' in division column\n<\/span>new_df <- df %>% filter(division %in%<\/span> my_values)\n\n#view results\n<\/span>new_df\n\n  assists points division\n1 West 120 30\n2 West 100 35\n3 North 105 23\n<\/span><\/span><\/strong><\/span><\/pre>\n
 Yeni veri \u00e7er\u00e7evesi yaln\u0131zca b\u00f6lme<\/strong> s\u00fctunundaki de\u011feri “Bat\u0131” veya “Kuzey”e e\u015fit olan sat\u0131rlar\u0131 i\u00e7erir.<\/span><\/p>\n
 Not<\/strong> : Temel R ve dplyr y\u00f6ntemleri ayn\u0131 sonu\u00e7lar\u0131 \u00fcretir. Ancak dplyr y\u00f6ntemi a\u015f\u0131r\u0131 b\u00fcy\u00fck veri \u00e7er\u00e7eveleriyle \u00e7al\u0131\u015f\u0131rken daha h\u0131zl\u0131 olma e\u011filiminde olacakt\u0131r.<\/span><\/p>\n
 Ek kaynaklar<\/strong><\/span><\/h3>\n
 A\u015fa\u011f\u0131daki e\u011fitimlerde R’de di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n
 Dplyr kullanarak R’de rastgele \u00e7izgiler nas\u0131l se\u00e7ilir<\/a>
 R’de ko\u015fula g\u00f6re sat\u0131rlar nas\u0131l se\u00e7ilir<\/a>
 R’deki herhangi bir s\u00fctunda de\u011ferin g\u00f6r\u00fcnd\u00fc\u011f\u00fc sat\u0131rlar nas\u0131l se\u00e7ilir<\/p>\n","protected":false},"excerpt":{"rendered":"
Bir vekt\u00f6r\u00fcn de\u011ferlerine g\u00f6re R’deki bir veri \u00e7er\u00e7evesinden sat\u0131r se\u00e7mek i\u00e7in a\u015fa\u011f\u0131daki y\u00f6ntemlerden herhangi birini kullanabilirsiniz: Y\u00f6ntem 1: Base R’yi kullan\u0131n new_df <- df[df$column_name %in% values_vector, ] Y\u00f6ntem 2: dplyr paketini kullanma library (dplyr) new_df <- df %>% filter(column_name %in% values_vector) A\u015fa\u011f\u0131daki \u00f6rnekler, R’deki a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesiyle her y\u00f6ntemin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir: #create data […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-3101","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\nC: Bir vekt\u00f6r\u00fcn de\u011ferlerine dayal\u0131 olarak veri \u00e7er\u00e7evesindeki sat\u0131rlar nas\u0131l se\u00e7ilir - 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